def saveContours(spectrum,
contourFile,
fileName,
levels,
firstInt,
lastInt,
isBigEndian=None):
from memops.c.StoreHandler import StoreHandler
import ccpnmr.c.ContourStyle as ContourStyle
import ccpnmr.c.ContourLevels as ContourLevels
# set things up
if isBigEndian is None or isBigEndian == isBigEndian():
swap = 0
else:
swap = 1
handler = StoreHandler(fileName, swap)
# below irrelevant but mandatory argument
pos_colors = neg_colors = [(0.0, 0.0, 0.0)]
contourStyle = ContourStyle.ContourStyle(pos_colors, neg_colors, 0, 0)
contourLevels = ContourLevels.ContourLevels(levels)
contourFile.draw(handler, firstInt, lastInt, contourLevels, contourStyle)
def createDataSource(self, experiment, name, dataUrl=None):
# set displayNames if available
ll = [dd.get('name') for dd in self.dimParams]
if [x for x in ll if x]:
# we have some displayNames
self.displayNames = ll
extraData = self.extraData
if extraData:
# set/override data from input extra parameters
for tag in dimParamDefs.keys() + extraDimParams:
val = extraData.get(tag)
if val:
setattr(self, tag, val)
# set referencing from carppm (carrier pm value)
carppm = extraData.get('carppm')
if carppm:
maxIndex = len(self.numPointsOrig) - 1
for ii, refppm in enumerate(carppm):
if self.refpt[ii] == 1.0:
# reset index to allow for the size arrays being shorter
# basically use last point by overshoot (project dimensions)
# skip if refpt !- 1.0, to preserve some user-set values
jj = min(ii, maxIndex)
refpt = self.numPointsOrig[
jj] / 2 + 1 - self.pointOffset[jj]
self.refpt[ii] = refpt
self.refppm[ii] = refppm
if self.ndim < 1:
raise ApiError('ndim = 0 (did you choose correct format?)')
# check that information compatible with experiment
if experiment.numDim != self.ndim:
raise ApiError(
'for now experiment numDim (%d) and dataSource numDim (%d) need to be the same'
% (experiment.numDim, self.ndim))
for n in range(self.ndim):
# TBD: is this correct? (e.g. do fidDimType have nuc?)
if self.dimType[n] != freqDimType:
if self.dimType[n] == fidDimType:
raise ApiError('dimension %s is FID - not yet supported.' %
(n + 1))
else:
self.nuc[n] = None
# match ExpDimRefs if any, to dims.
expDims = experiment.sortedExpDims()
for n in range(self.ndim):
expDim = expDims[n]
if self.dimType[n] == freqDimType:
if expDim.expDimRefs:
if len(expDim.expDimRefs) == 1:
expDimRef = expDim.findFirstExpDimRef()
if (self.nuc[n]):
if expDimRef.isotopeCodes != (self.nuc[n], ):
print(
'Warning: in dim %d experiment has isotopeCodes %s, spectrum has %s, must be the same'
% (n + 1, expDimRef.isotopeCodes,
(self.nuc[n], )))
if (abs(expDimRef.sf - self.sf[n]) > 1.0e-2):
print(
'Warning: inconsistent sf in dim %d: %3.2f vs %3.2f'
% (n + 1, expDimRef.sf, self.sf[n]))
elif expDimRef.isotopeCodes:
print(
'Warning: in dim %d experiment has isotopeCodes %s, spectrum has no nuc set'
% (n + 1, expDimRef.isotopeCodes))
else:
# NBNB TBD new code - may not work for all cases
if (self.nuc[n]):
expDimRef = None
expDimRefs = [
x for x in expDim.sortedExpDimRefs()
if x.isotopeCodes == (self.nuc[n], )
]
for xdr in expDimRefs:
if abs(xdr.sf - self.sf[n]) <= 1.0e-2:
expDimRef = xdr
break
elif not xdr.sf:
expDimRef = xdr
if expDimRef is None:
if expDimRefs:
expDimRef = expDimRefs[0]
print(
'Warning: in dim %d no ExpDimRef fits sf %s'
% (n + 1, self.nuc[n]), expDimRef.sf,
self.sf[n])
else:
expDimRef = expDim.findFirstExpDimRef()
print(
'Warning: in dim %d no ExpDimRef fits nucleus %s'
% (n + 1, self.nuc[n]), expDimRef.sf,
self.sf[n])
else:
expDimRef = expDim.findFirstExpDimRef()
print(
'Warning: in dim %d spectrum has no nuc set' %
(n + 1))
else: # non-freq dim
if expDim.expDimRefs:
raise ApiError('non-freq dim has experiment dim ref')
if self.dataFile:
# create DataStore
memopsRoot = experiment.root
if dataUrl:
preferDataUrls = [dataUrl]
else:
oldDataStores = (x.dataStore for x in experiment.dataSources)
preferDataUrls = set(x.dataUrl for x in oldDataStores if x)
newDataUrl, filePath = getDataStoringFromFilepath(
memopsRoot,
self.dataFile,
preferDataUrls=preferDataUrls,
keepDirectories=self.keepDirectories)
if dataUrl is not None and newDataUrl is not dataUrl:
raise ApiError("DataUrl with path %s not valid for file %s" %
(dataUrl.url.path, self.dataFile))
dataLocationStore = newDataUrl.dataLocationStore
if self.big_endian is not None:
bigEndian = self.big_endian
elif self.swap:
bigEndian = not isBigEndian()
else:
bigEndian = isBigEndian()
if self.integer:
numberType = 'int'
else:
numberType = 'float'
isComplex = [
self.dimParams[ii].get('isComplex') for ii in range(self.ndim)
]
if None in isComplex:
isComplex = self.ndim * [False]
# numPoints - necessary in case of projection spectra
numPoints = self.npts
if None in numPoints:
numPoints = numPoints[:numPoints.index(None)]
params = {
'dataUrl': newDataUrl,
'path': filePath,
'numPoints': numPoints,
'isBigEndian': bigEndian,
'numberType': numberType,
'isComplex': isComplex,
'headerSize': self.head,
'fileType': self.format,
'nByte': self.nbytes,
}
if self.format == 'Factorised':
for tag in ('numShapes', 'isReconstructable', 'isResolved',
'numRecords'):
if tag in self.topParams:
params[tag] = self.topParams[tag]
dataStore = dataLocationStore.newShapeMatrix(**params)
# NBNB TBD assumes there are no 2D shapes. To be changed!
if len(self.dimParams) == self.topParams['numShapes']:
# all shapes are 1D
for dim in range(self.topParams['numShapes']):
dataStore.newComponentShape(dims=(dim, ))
else:
raise ApiError(
"Decompositions must have one shape per dim (for now)")
# add Component elements
for dd in self.topParams['componentList']:
dataStore.newComponent(**dd)
else:
# default: blocked binary matrix
if self.blockHead:
params['blockHeaderSize'] = self.blockHead
# blockSizes - necessary in case of projection spectra
blockSizes = self.block
if None in blockSizes:
blockSizes = blockSizes[:blockSizes.index(None)]
# Bruker in Topspin 3 can have blockSize = 0 it seems
for nn, blockSize in enumerate(blockSizes):
if blockSize == 0:
blockSizes[nn] = numPoints[nn]
dataStore = dataLocationStore.newBlockedBinaryMatrix(
blockSizes=blockSizes, **params)
else:
dataStore = None
#set ndims and set up for extra (projection) dims
ndims = self.ndim
lastEdrs = expDims[-1].expDimRefs
if (self.nAxes > ndims and self.dimType[-1] == freqDimType
and (not lastEdrs or self.nAxes <= ndims + len(lastEdrs))):
# We have extra (projection) ExpDimRefs,
# They fit onto existing, or the last dimension still needs ExpDimRefs
# Set up to add extra ExpDimRefs to last ExpDim
expDims.extend((self.nAxes - ndims) * [expDims[-1]])
ndims = self.nAxes
#set ExpDimRefs and isAcquisition
hasNoAcqDim = (
expDims[0].experiment.findFirstExpDim(isAcquisition=True) is None)
for n in range(ndims):
if self.dimType[n] == freqDimType:
expDim = expDims[n]
lenExpDimRefs = len(expDim.expDimRefs)
if (not lenExpDimRefs or (n >= self.ndim + lenExpDimRefs - 1)):
# The first term ensures an ExpDimRef for every freqDim
# The second adds extra expDimRefs to the last Dim to use up all
# read Dims (for projection experiments
if hasNoAcqDim and n == self.acquisitionDim:
expDim.isAcquisition = True
hasNoAcqDim = False
if self.nuc[n]:
xdr = expDim.newExpDimRef(
sf=self.sf[n],
unit='ppm',
baseFrequency=self.baseFreq[n],
isotopeCodes=[self.nuc[n]])
else:
xdr = expDim.newExpDimRef(
sf=self.sf[n],
unit='None',
baseFrequency=self.baseFreq[n],
)
# set displayName
if hasattr(self, 'displayNames'):
displayNames = self.displayNames
if displayNames:
ii = 0
for expDim in experiment.sortedExpDims():
for expDimRef in expDim.sortedExpDimRefs():
expDimRef.displayName = displayNames[ii]
ii += 1
dataSource = experiment.newDataSource(name=name,
numDim=self.ndim,
dataStore=dataStore,
dataType='processed',
scale=self.scale)
scalingFactors = None
if hasattr(self, 'scalingFactors'):
ll = self.scalingFactors
if ll:
scalingFactors = ll
# Set DataSource.DataDims
for n in range(self.ndim):
sw = self.sw[n]
npts = self.npts[n]
numPointsOrig = self.numPointsOrig[n] or npts
expDim = expDims[n]
if self.dimType[n] == freqDimType:
freqDataDim = dataSource.newFreqDataDim(
dim=n + 1,
numPoints=npts,
isComplex=False,
numPointsOrig=numPointsOrig,
pointOffset=self.pointOffset[n],
valuePerPoint=sw / float(npts),
expDim=expDim)
expDimRef = expDim.findFirstExpDimRef()
ddr = freqDataDim.newDataDimRef(refPoint=self.refpt[n],
refValue=self.refppm[n],
expDimRef=expDimRef)
# reset to reference on O1
centrePoint = freqDataDim.numPointsOrig / 2 - freqDataDim.pointOffset + 1
ddr.refValue = ddr.pointToValue(centrePoint)
ddr.refPoint = centrePoint
if scalingFactors is not None:
# NB DimensionScaling is set automatically in some cases
previousDimScaling = freqDataDim.findFirstDimensionScaling(
expDimRef=expDimRef)
if previousDimScaling is None:
freqDataDim.newDimensionScaling(
expDimRef=expDimRef,
scalingFactors=(scalingFactors[n], ))
else:
previousDimScaling.scalingFactors = (
scalingFactors[n], )
elif self.dimType[n] == fidDimType:
raise ApiError('fidDimType not supported yet')
elif self.dimType[n] == sampledDimType:
# TBD: set conditionVaried somehow
dataSource.newSampledDataDim(dim=n + 1,
numPoints=npts,
isComplex=False,
pointValues=self.pointValues[n],
expDim=expDim)
else:
raise ApiError('%s dimType not supported yet' %
self.dimType[n])
# Add extra (projection) DataDimRefs to last dataDim
# NB if ndims > self.ndim the last dimension is a freqDataDim
# freqDataDim, expDim, and npts come correctly out of the preceding loop.
expDimRefs = expDim.sortedExpDimRefs()
ii = 0
for n in range(self.ndim, ndims):
ii += 1 # NB we do want to start with expDimRefs[1]
expDimRef = expDimRefs[ii]
ddr = freqDataDim.newDataDimRef(refPoint=self.refpt[n],
refValue=self.refppm[n],
expDimRef=expDimRefs[ii],
localValuePerPoint=self.sw[n] /
npts)
# reset to reference on O1
centrePoint = freqDataDim.numPointsOrig / 2 - freqDataDim.pointOffset + 1
ddr.refValue = ddr.pointToValue(centrePoint)
ddr.refPoint = centrePoint
if scalingFactors is not None:
freqDataDim.newDimensionScaling(
expDimRef=expDimRef, scalingFactors=(scalingFactors[n], ))
#
return dataSource
byte_order = [0x40, 0x16, 0x14, 0x7b]
t = [ord(c) for c in s[8:12]]
if (t == byte_order):
big_endian = True
else:
t.reverse()
if (t == byte_order):
big_endian = False
else:
raise ApiError(
'bytes 8 through 11 should be [ 0x40, 0x16, 0x14, 0x7b ] or reverse'
)
big_endian = big_endian
swap = not (big_endian == isBigEndian())
if (swap):
x.byteswap()
return (s, x, big_endian, swap)
def getDataFileName(template, z, a=None):
"""Get NMRPipe fileName given template and z and (optionally) a.
Note that z and a start counting at 0, not 1.
"""
if a is None:
name = template % (z + 1)
else:
def createDataSource(self, experiment, name, dataUrl=None):
# check that information compatible with experiment
if experiment.numDim != self.ndim:
raise ApiError('for now experiment numDim (%d) and dataSource numDim (%d) need to be the same' % (experiment.numDim, self.ndim))
for n in range(self.ndim):
# TBD: is this correct? (e.g. do fidDimType have nuc?)
if self.dimType[n] != self.freqDimType:
self.nuc[n] = None
expDims = experiment.sortedExpDims()
useExpDimRefs = [None] * self.ndim
for n in range(self.ndim):
expDim = expDims[n]
if self.dimType[n] == self.freqDimType:
if expDim.expDimRefs:
if len(expDim.expDimRefs) == 1:
#raise ApiError('for now can only have one experiment dim ref')
expDimRef = expDim.findFirstExpDimRef()
useExpDimRefs[n] = expDimRef
if (self.nuc[n]):
if expDimRef.isotopeCodes != (self.nuc[n],):
print 'Warning: in dim %d experiment has isotopeCodes %s, spectrum has %s, must be the same' % (n+1, expDimRef.isotopeCodes, (self.nuc[n],))
if (abs(expDimRef.sf-self.sf[n]) > 1.0e-2):
print 'Warning: inconsistent sf in dim %d: %3.2f vs %3.2f' % (n+1, expDimRef.sf, self.sf[n])
elif expDimRef.isotopeCodes:
print 'Warning: in dim %d experiment has isotopeCodes %s, spectrum has no nuc set' % (n+1, expDimRef.isotopeCodes)
else:
# NBNB TBD new code - may not work for all cases
if (self.nuc[n]):
expDimRef = None
expDimRefs = expDim.findAllExpDimRefs(isotopeCodes=(self.nuc[n],))
for xdr in expDimRefs:
if abs(xdr.sf-self.sf[n]) <= 1.0e-2:
expDimRef = xdr
break
elif not xdr.sf:
expDimRef = xdr
if expDimRef is None:
expDimRef = expDim.findFirstExpDimRef()
print (
'Warning: in dim %d no ExpDimRef fits nucleus %s' % (n+1, self.nuc[n])
, expDimRef.sf, self.sf[n]
)
else:
expDimRef = expDim.findFirstExpDimRef()
print (
'Warning: in dim %d spectrum has no nuc set' % (n+1)
)
else: # non-freq dim
if expDim.expDimRefs:
raise ApiError('non-freq dim has experiment dim ref')
if self.dataFile:
memopsRoot = experiment.root
# create DataStore
if dataUrl:
preferDataUrls = [dataUrl]
else:
oldDataStores = (x.dataStore for x in experiment.dataSources)
preferDataUrls = set(x.dataUrl for x in oldDataStores if x)
newDataUrl, filePath = getDataStoringFromFilepath(memopsRoot,
self.dataFile, preferDataUrls=preferDataUrls,
keepDirectories=self.keepDirectories)
if dataUrl is not None and newDataUrl is not dataUrl:
raise ApiError("DataUrl with path %s not valid for file %s"
% (dataUrl.url.path, self.dataFile) )
dataLocationStore = newDataUrl.dataLocationStore
if self.big_endian is not None:
bigEndian = self.big_endian
elif self.swap:
bigEndian = not isBigEndian()
else:
bigEndian = isBigEndian()
if self.integer:
numberType = 'int'
else:
numberType = 'float'
isComplex = [self.dimParams[ii].get('isComplex')
for ii in range(self.ndim)]
if None in isComplex:
isComplex = self.ndim * [False]
params = {
'dataUrl':newDataUrl, 'path':filePath, 'numPoints':self.npts,
'isBigEndian':bigEndian, 'numberType':numberType, 'isComplex':isComplex,
'headerSize': self.head
}
dataStoreType = self.topParams.get('dataStoreType')
if dataStoreType == 'factorised':
dataStore = dataLocationStore.newShapeMatrix(
numRecords=self.topParams['numRecords'], **params)
# NBNB TBD assumes there are no 2D shapes. To be changed!
for dim in range(len(self.dimParams)):
dataStore.newComponentShape(dims = (dim,))
else:
dataStore = dataLocationStore.newBlockedBinaryMatrix(
blockSizes=self.block, **params)
# TBD: TEMP: use appData until blockHeaderSize is in data model
if self.blockHead and hasattr(dataStore.root, 'application'):
dataStore.root.application.setValue(dataStore, 'blockHeaderSize', self.blockHead)
else:
dataStore = None
for n in range(self.ndim):
expDim = expDims[n]
if not expDim.expDimRefs and self.dimType[n] == self.freqDimType:
if self.nuc[n]:
expDim.newExpDimRef(sf=self.sf[n], unit='ppm', isotopeCodes=[self.nuc[n]])
else:
expDim.newExpDimRef(sf=self.sf[n], unit='None')
dataSource = experiment.newDataSource(name=name, numDim=self.ndim,
dataStore=dataStore,
dataType='processed')
for n in range(self.ndim):
sw = self.sw[n]
npts = self.npts[n]
expDim = expDims[n]
if self.dimType[n] == self.freqDimType:
freqDataDim = dataSource.newFreqDataDim(dim=n+1, numPoints=npts, isComplex=False,
numPointsOrig=npts, valuePerPoint=sw/float(npts), expDim=expDim)
freqDataDim.newDataDimRef(refPoint=self.refpt[n],
refValue=self.refppm[n],
expDimRef=expDim.findFirstExpDimRef())
elif self.dimType[n] == self.fidDimType:
raise ApiError('fidDimType not supported yet')
elif self.dimType[n] == self.sampledDimType:
# TBD: set conditionVaried somehow
dataSource.newSampledDataDim(dim=n+1, numPoints=npts, isComplex=False,
pointValues=self.pointValues[n], expDim=expDim)
else:
raise ApiError('%s dimType not supported yet' % self.dimType[n])
return dataSource
class UcsfParams(ExternalParams):
format = 'UCSF'
def __init__(self, file, **kw):
self.dataFile = file
ExternalParams.__init__(self, **kw)
# ExternalParams requires this to be defined
def parseFile(self):
try:
fp = open(self.dataFile, 'rb')
except IOError, e:
raise ApiError(str(e))
s = fp.read(ucsf_file_header)
if (len(s) < ucsf_file_header):
raise ApiError('file shorter than expected length (%d bytes) of first part of header (never mind data)' % ucsf_file_header)
if (s[:8] != 'UCSF NMR'):
raise ApiError('first eight bytes of header = "%s", should be "UCSF NMR"' % s[:8])
ndim = self.ndim = ord(s[10])
self.head = ucsf_file_header + ndim*ucsf_dim_header
self.big_endian = True # UCSF files always big endian
self.swap = not isBigEndian()
s = fp.read(ndim*ucsf_dim_header)
if (len(s) < ndim*ucsf_dim_header):
raise ApiError('file shorter than expected length (%d bytes) of header (never mind data)' % (ucsf_file_header+ndim*ucsf_dim_header))
fp.close()
x = array.array('i')
y = array.array('f')
x.fromstring(s)
y.fromstring(s)
if (self.swap):
x.byteswap()
y.byteswap()
self.initDims()
for i in range(ndim):
j = ndim - i - 1 # UCSF does dims backwards
base = (j * ucsf_dim_header) / 4
self.npts[i] = x[base+2]
self.block[i] = x[base+4]
self.sf[i] = y[base+5]
self.sw[i] = y[base+6]
self.refppm[i] = y[base+7]
# 27 Oct 2006: added 1.0, which seems to be the correct thing to do
self.refpt[i] = 1.0 + 0.5 * float(self.npts[i])
nuc = s[4*base:4*base+6]
n = nuc.find(chr(0))
if (n >= 0):
nuc = nuc[:n]
self.nuc[i] = self.standardNucleusName(nuc)